Highlights Conceptualizes and defines person-trip shareability, which is mode-agnostic. Operationalizes person-trip shareability through maximizing overlap of OD trips on network links. Unifies travel demand and network supply to quantify a geographic region’s sharing potential. Formulates fundamental network property—maximum flow overlap—with quadratic program. Finds that overlap-based shareability metrics are strongly associated with microtransit efficiency.
Abstract Cities around the world vary in terms of the structure of their transportation networks and travel demand patterns. Despite these variations significantly impacting opportunities for travelers to share trips, no metrics are available to jointly characterize a region’s transportation network and travel demand in terms of the potential for travelers to share space with each other on network links, or what we call person-trip shareability. This study proposes metrics to quantify the shareability of person-trips in a city subregion, as a function of three inputs—the underlying transportation network, origin–destination (OD) travel demand, and a maximum permissible detour parameter. After defining person-trip shareability and providing principles for operationalizing this definition, we formulate a fundamental metric, called flow overlap. Flow overlap measures, for a person-trip traversing a given path, the weighted (by link distance) average number of other person-trips sharing the links along the original person-trip’s path. We then formulate the Maximum Network Flow Overlap Problem (MNFLOP), a math program that assigns person-trips to network paths that maximize network-wide flow overlap. We utilize the MNFLOP output to calculate shareability metrics at various levels of aggregation: person-trip level, OD level, origin or destination level, network level, and link level. The study applies the MNFLOP and associated shareability metrics to different OD demand scenarios in the Sioux Falls network. The computational results verify that MNFLOP (i) assigns person-trips to paths such that flow overlaps significantly increase relative to shortest path assignment, (ii) can meaningfully differentiate between different OD trip matrices in terms of flow overlap, and (iii) metrics can meaningfully quantify demand dispersion from a single network node/location considering the underlying road network. Finally, we validate MNFLOP’s ability to quantify shareability by showing that demand patterns with higher flow overlap are strongly associated with lower mileage routes for a last-mile microtransit service. The paper includes an extensive discussion of other potential future uses of the MNFLOP and its associated shareability metrics.
Metrics for Quantifying Shareability in Transportation Networks: The Maximum Network Flow Overlap Problem
2023-11-16
Article (Journal)
Electronic Resource
English
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